Application of social network analysis in transportation network based on AIS data

Ouyang Pengfei, Yi Zuo, Junhao Jiang, Peng Jia

Abstract: This article aims to explore ways to improve the efficiency and management of maritime transportation by analyzing the key nodes within the Bohai Bay maritime transportation network and their impact on the network structure. Using the container ship data of the Bohai Bay in the first half of 2018, the Bohai Bay is divided into a 100×100 grid. The ship trajectory points within this grid serve as nodes, the ship trajectories as edges, and the frequency of these trajectories as the weight of the edges, thereby constructing a comprehensive network. The community detection method is used to identify the top four communities with the largest number of nodes, while the z-P matrix is used to categorizes the nodes within each community into different roles. In the experiment, the top 10 nodes ranked by weighted degree, closeness centrality, and betweenness centrality, along with provincial and connector hubs, were systematically removed. Subsequently, the average clustering coefficient and average path length of the community and the entire network before and after deletion of key nodes were analyzed. The study found that the removal of key nodes exerts a markedly different impact on different communities and the entire network, thereby offering valuable theoretical support and practical guidance for maritime traffic management.

Submission Number: 40